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Architecture and application of nanorobots in medicine
CHAPTER THIRTEEN
Architecture and application of nanorobots in medicine Ramna Tripathia, Amit Kumarb and Akhilesh Kumarc a
Department of Physics, THDC-Institute of Hydropower Engineering & Technology, Tehri, India Department of ECE, THDC-Institute of Hydropower Engineering & Technology, Tehri, India Department of Physics, Govt. Girls P. G. College, Lucknow, India
b c
1 Introduction In a prescient talk in 1959, the late Nobel physicist Richard P. Feynman said, “There’s Plenty of Room at the Bottom,” and proposed to make miniature machine apparatuses and use these apparatuses to make still smaller machine apparatuses and so on, all the way down to the atomic level. Feynman was very much clear about the possible medical applications of the new technology. He added: “A friend of mine (Albert R. Hibbs) suggests a very interesting possibility for relatively small machines. He says that, although it is a very wild idea, it would be interesting in surgery if you could swallow the surgeon. You put the mechanical surgeon inside the blood vessel and it goes into the heart and looks around. It finds out which valve is the faulty one and takes a little knife and slices it out. Other small machines might be permanently incorporated in the body to assist some inadequately functioning organ.”
Later, in his subsequent lecture in the same year, Feynman proposed the option of linking with biological cells and said, “We can manufacture an object that maneuvers at that level!” The vision of Feynman come to be a reality after the publishing of a technical paper by Eric Drexler in which he suggested that it might be possible to build nanodevices from biological parts that could examine and repair the cells of a human being. The exploration was followed a decade later by Drexler’s technical book laying the foundations of molecular machines and molecular manufacturing systems (Drexler, 1986, 1992; Drexler et al., 1991) and subsequently supported by Freita’s technical books on medical nanorobotics (Freitas, 1999, 2003, 2005). Control Systems Design of Bio-Robotics and Bio-mechatronics with advanced applications https://doi.org/10.1016/B978-0-12-817463-0.00013-7
© 2020 Elsevier Inc. All rights reserved.
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In the earlier 1990s, very little scientific work was done on nanorobotics, and was mostly based on concept generation, architecture, and modeling. Since then, many research papers have been published on systematic computational and experimental studies on nanorobotics. Nowadays, the field of nanorobotics keeps expanding and many scientists and researchers in their laboratories all over the world are focusing their activities on it. Nanorobotics became known to the public via science fiction movies, television, and books. In 1966, Isaac Asimov published a book entitled Fantastic Voyage, in which he described a minuscule submarine capable of moving through the human bloodstream (Asimov, 1966), while in 2002, in the very popular book, Prey, Michael Crichton introduced a swarm of intelligent nanorobots that threaten humankind (Crichton, 2002). Even though the concept of nanorobotics being described in this book is not at all related with the actual theory of nanorobots, it helped to generate public interest, which is important for the future growth of the field. Nanorobotics is a comparatively new field that grew out of the merging of robotics and nanotechnology during the late 1990s and early 2000s. The term nanorobot was being used by the scientific community in the broadest possible way in the late 1990s, because this term included any type of active structure capable of anyone of the following, or any of them in combination: actuation, sensing, manipulation, propulsion, signaling, information processing, intelligence, and swarm behavior at the nanoscale. The term nanorobot includes large-scale manipulators with nanoscale precision accuracy and manipulation capabilities and micro-scale robotic devices with at least one nanoscale component (Weir et al., 2005). Nanorobots are basically theoretical microscopic devices built on nanometer dimensions (109 m). When nanorobotics has fully realized its potential from the current theoretical stage, nanorobots will work at atomic, molecular, and cellular level to perform tasks in both medical and industrial fields. This came as a natural evolution of the micro-robotics field that grew rapidly in the 1990s and of the nanotechnology field that exploded in the 2000s. Some of the most primitive appearances of the term occur in 1998 in the paper by Requicha et al. that focused on nanorobotic assembly (Requicha et al., 1998); Sitti and Hashimoto’s paper on tele-nanorobotics (Sitti et al., 1998); and in 1999, Freitas’ book on nanomedicine, where one can find a nice historical presentation of the nanorobotic concept for medical applications (Freitas, 1999). Prior to 1998, the term nanorobot had been clearly described by several researchers and was referred to as a “molecular machine,” “nanomachine,” or “cell repair machine” (Wowk, 1988; Dewdney, 1988).
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This chapter emphasizes developments in the evolving domain of nanorobotics in medicine, especially on the design and application of cancer and cerebral aneurysm.
2 Design of nanorobotic systems for cancer therapy Important parameters used for medical nanorobotic architecture and its control activation, along with essential technological background for advance manufacturing hardware for molecular machines are described below.
2.1 Mechanized technology In manufacturing technology, complementary metal oxide semiconductorvery large scale integration (CMOS-VLSI) and verification hardware description language (VHDL) are playing an important role. The CMOS industry is guiding a pathway for assembly processes needed to manufacture components required to enable nanorobots, whereas to confirm the designs and to achieve a fruitful implementation, VHDL is being utilized in the integrated circuit manufacturing industry.
2.2 Chemical sensor In the past decade, production of silicon-based chemical sensor and motion sensor arrays with the use of two-level system architecture hierarchy has been successfully achieved. These sensors are in widespread use from automotive to chemical industries for detection of air, water, element, and pattern recognition through embedded software programming and biomedical uses. Similarly the use of nanotechnology is also groom in this field as nanowires which decreased the estimated cost of energy demanded for data transfer and circuit operation by up to 60%. The CMOS-based biosensors using nanowires as material for circuit assembly can achieve superior efficiency for applications in detecting chemical changes, thus enabling medical treatment with increased precision and effectiveness. CMOS devices of 90 and 45 nm represent breakthrough technology devices that are being applied in manufacturing of nanorobots. Discovery or development of new materials such as strained channel with relaxed SiGe layer can reduce self-heating and improve the performance of nanorobots. In advance manufacturing techniques, silicon on insulator (SOI) technology has also been used to assemble high-performance logic sub 90 nm circuits. Circuit design methods to
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resolve bipolar effects and hysteretic variations based on SOI structures have been verified positively. In addition, chemical nanosensors can be implanted in nanorobots to monitor epithelial cadherin gradients. E-cadherin (or Cadherin-1, or CAM 120/80, or Uvomorulin) is a protein in the human body, encoded by the CDH1 (tumor suppressor) gene, which is designated as cluster of differentiation 324. Evolution of cancer and metastasis is directly proportional of loss of E-cadherin, which means E-cadherin down regulation decreases the strength of cellular adhesion within a tissue, causing an increase in cellular motility, which allows cancer cells to cross the basement membrane and invade surrounding tissues. E-cadherin is also used by pathologists to diagnose different kinds of breast cancer. When compared with invasive ductal carcinoma, E-cadherin expression is markedly reduced or absent in the great majority of invasive lobular carcinomas when studied by immunohistochemistry. Nanorobots programmed for these tasks can perform detailed screening of the whole body of the patient. In this biomedical nanorobotic architecture, cellphones are used to retrieve patient information. A cellular application uses electromagnetic waves to command and detect the current status of nanorobots inside the patient’s body. Contemporary advancement in FinFETs, double-gates, and 3D circuit technologies is capable of accomplishing surprising outcomes, which are expected to develop further.
2.3 Power supply Active telemetry and power supply is the most effective and secure method of sustained energy supply for nanorobots in operation using CMOS. A similar procedure is also suitable for digital bit encoded data transfer from inside the human body. It can be understood that nanocircuits with resonant electric properties can operate as a chip providing electromagnetic energy and supplying 1.7 mA at 3.3 V for power, allowing the operation of many tasks with very few or no power losses during the transmission. By utilizing a techniques that is widely used for commercial applications of radio frequency identification devices (RFID), with the use of inductive coupling, RF-based telemetry procedures have demonstrated encouraging results in patient monitoring and power transmission. In this procedure, the energy savings can be in the ranges of 1 μW when the nanorobot is in inactive modes, and gets activated when signal patterns require it to do so. Some general nanorobotic tasks may require the device only to utilize low amounts of
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power once it has been strategically activated, for example, only 1 mW RF signal required for communication. The easiest way to implement this architecture is by cellphone, which should be uploaded with the control software that includes the communication and energy transfer protocols, gaining both energy and data transfer capabilities.
2.4 Data transmission The implanted devices and integrated sensors inside the human body to transmit health data of patients will provide exceptional advantage in constant medical monitoring. RFID chips have been developed as an integrated circuit device for medicine, and RFID for in vivo data collection and transmission has been successfully tested for electroencephalograms. Many researchers and scientists are working on single chip RFID CMOS-based sensors because CMOS with submicron SoC design may be used for very low power consumption in nanorobotic communication over longer distances through acoustic sensors. Nanorobots’ active sonar communication frequencies may reach up to 20 μW@8 Hz at resonance rates with 3 V supply. In molecular machine architectures, to implant an embedded antenna for nanorobot RF communication with 200 nm size, a small loop planar device is adopted as an electromagnetic pick-up. It also has a good matching on low noise amplifier and is developed on gold nanocrystal with 1.4 nm3 CMOS and nanoelectronics circuit technologies. Frequencies in the range of 1–20 MHz can be fruitfully used in biomedical applications without any damage to the device.
3 System implementation Real-time 3D prototyping and simulation tools have significant benefits in nanotechnological developments because these tools have helped the semiconductor industry to attain faster VLSI developments. Simulation can anticipate the performance and provide support in device design, manufacturing, nanomechatronics control design, and hardware implementation. The simulation includes the nanorobot control design (NCD) software for nanorobot sensing and actuation, whereas nanorobot architectures include integrated nanoelectronics. The nanorobot architecture involves the use of cellphones for the early diagnosis of E-cadherin levels for smart chemotherapy drug delivery and in new tumor detection for cancer treatments. Nanorobots use an RFID CMOS transponder system for in vivo positioning using wellestablished communication protocols that allow tracking information about
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the nanorobot position and this information will help doctors in detecting tiny malignant tissues in the initial stages of development. The exterior of nanorobots is made up of diamondoid material, to which may be attached an artificial glycocalyx surface. The exterior material minimizes fibrinogen (and other blood proteins) adsorption and bioactivity, ensuring sufficient biocompatibility to avoid immune system attack. Various types of molecules have been distinguished by a series of chemotactic biosensors whose binding sites have a different affinity for each kind of molecule. These sensors are also capable of detecting obstacles that might require new trajectory planning for nanorobots. Nanorobots with sensory capabilities are able to detect and identify changes of E-cadherin proteins gradients beyond permissible levels, which guide the nanorobots in detecting tumors even at early stages of cancer. There could be a variety of such sensors, for instance, chemical detection can be very selective for identifying various types of cells by their markers. In acoustic sensing, different frequencies are detected, which have different wavelengths depending on object sizes of attention.
4 Chemical signals inside the body Depending on the requirement of communication in liquid workspaces, acoustic, light, RF and chemical signals are considered as probable alternatives for communication and data transmission. E-cadherin is a chemical signaling, which act as a transmission media between nanorobots. Chemical signals and their interaction with the bloodstream are a very important aspect to manage the application of nanorobots in cancer therapy. The signal sensing of nanorobots for simulated architecture in detecting gradient changes on E-cadherin signals are examined. In order to improve response and bio sensing capabilities, nanorobots maintain positions near the vessel wall instead of floating throughout the vessel in the volume flow. The vein wall is modeled with a grid texture to enable better depth and distance perception in the 3D workspace. Another significant choice in chemical signaling is the measurement of time and detection of threshold at which the signal is considered to be received. Because of background concentration, some detection occurs even in the absence of the target signal. With threshold, diffusive capture rate (α) is used, for a sphere of radius (R) in a region with concentration as (the concentration for other shapes such as cylinders is about the same): α ¼ 4πDRC
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With autonomous random motions for the molecules, detection over a time interval (Δt) is a Poisson process with mean value αΔt. Table 1 shows the different parameters with chemical signals that one can use to find out the variables related with this concept. Scientists have discovered that, with the plaque on the vessel wall, fluid velocity near the target is lower than the average velocity. When the nanorobot first detects a tumor for medical treatment, the nanorobot is programmed to attach on the tumor cell. The nanorobotic architecture is designed to send wireless communication about the accurate position of the tumor to the doctors. Then a predefined number of other nanorobots to support in perceptive chemotherapeutic action with precise drug delivery above the tumor are called for by sending signals. In a similar manner to quorum sensing in bacteria, it starts from monitoring the concentration of signals, chemical substances for near communication will attract or repeal nanorobots, and also estimates the number of nanorobots at the target. Due to this, nanorobots stop attracting other nanorobots when a sufficient number of nanorobots have responded to the initial signal. The amount of nanorobots can be changed depending on the stage of cancer and the tumor size, and may be defined by the oncologist based on the information received from the nanorobots through RF electromagnetic waves. The nanorobots at the plaque emit a different signal than others not already at the target, which is interpreted as an indication that others no longer need to respond. This mechanism allows them to be free to further search for other malignant tissues inside the body. Nanorobots will empower drug delivery and are also loaded with therapeutic
Table 1 Chemical signal and parameters. Chemical signals
Production rate (Q) Diffusion coefficient (D) Background concentration (C)
104 molecules/s 100 μm2/s 6 103 molecules/(μm)3
Parameters
Values
Average fluid velocity (v) Vessel diameter (d) Workspace length (L) Density of cells Nanorobot
1000 μm/s 20 μm 50 μm 2.5 103 cell/(μm)3 2 μm3
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chemicals, preventing the cancer from spreading further. The following control mechanisms are being considered: • Random: Nanorobots moving inactively with the fluid reaching the target only if they bump into it due to Brownian motion. • Follow gradient: Nanorobots monitor concentration intensity of E-cadherin signals when detected; they measure and follow the gradient until they reach the target. If the gradient estimate finds no additional signal in 50 ms, the nanorobot considers the signal to be a false positive signal and continues flowing with the fluid. • Follow gradient with attractant: In addition to the previous mechanism, nanorobots arriving at the target release a different chemical signal, which is used by others to improve their ability to find the target. This mechanism involving peer-to-peer communication amongst the nanorobots is highly pertinent for improving nanorobotic performance.
5 Simulator results Consider a fluid moving with uniform velocity (v) in the positive x axis direction. It contains a point source of chemical production rate (Q) in molecules per second. The diffusion coefficient is represented by D, and the diffusion equation is: Dr2 C ¼ v∂C=∂x With the boundary conditions of a steady point source at the origin and distance to the chemical signal source (r ¼ √ x2 + y2 + z2) and no net flux across the boundary plane (y ¼ 0), determines the steady-state concentration (C), i.e., time during which concentration (molecules/μm3) remains stable or consistent, at point (x, y, z) is: C ðx, y, zÞ ¼ ðQ=2πDr ÞevðrxÞ=2D In nanorobotic behavior the fluid flow pushes the concentration of diffusing signal downstream. Subsequently, a nanorobot at more than a few microns away from the source won’t detect the signal while it is still relatively near the source. By taking the parameters from Table 1, one can detect an average higher signal concentration within about 10 ms when nanorobots are close enough. Thus, keeping their motion near the vessel wall, the signal detection happens after nanorobots have moved around 10 μm past the source. Thus, nearly
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five nanorobots per second arrive at the tumor cell in the small venule, which is one among many types of vessels present in the human body. A design trade-off for chemical signals the nanorobots could release is designed by the equation C(x, y, z) ¼ (Q/2πDr)e v(r x)/2D. Additional signals will use other molecules, which could, by design, have a different diffusion coefficient to use instead of the diffusion coefficient associated with the chemical from the target. From this equation, the effect of the fluid motion becomes significant at distances; this means that faster diffusion results in lower concentrations, demanding more time for other nanorobots to determine gradients. In future, if the signals are increasing in a steady, constant, and progressive manner, then chemical diffusion could be more efficient for nanorobotic communication. The nanorobots strike the target, if passing inside the human body, with a speed of nearly 0.1 μm. The nanorobots crossing within a few microns often detect the signal, which spreads a bit further upstream and away from the single tumor due to the slow fluid motion near the venule’s wall and the cell’s motion. Nanorobots flowing closer to the wall also benefit from slower fluid motion near the walls by having more time to detect signals. An “attractant” signal with the same value of D as the original signal has been used. Each nanorobot can release at one-tenth the rate of the target over the time. Individual performance has been observed throughout a set of analyses obtained from the NCD software, in which nanorobots use chemical sensors as the communication technique to interact dynamically in a 3D environment and to achieve a positive collective coordination. The virtual environment comprised of a small venule vessel that contains nanorobots, red blood cells (RBCs), and a single tumor cell, which is the target area on the vessel wall. Here, the target area is overlapped by the RBCs. Table 2 provides a summary and comparison of the control techniques evaluated using the NCD simulator with the time required for 10 nanorobots and 20 nanorobots to identify and reach the target. Each value is the mean of 30 repetitions in simulation, with standard deviation in parentheses. The error estimate for these mean values is Table 2 Nanorobots: times in seconds to reach the target.
Control method Random motion Follow gradient Gradient with “attractant”
Nanorobots (10) 0.73 (0.18) 0.54 (0.17) 0.46 (0.13)
Nanorobots (20) 1.47 (0.28) 1.14 (0.24) 0.79 (0.14)
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√ 30 times smaller than the standard deviations listed here. For comparison, if every nanorobot passing through the vessel found the target, 20 nanorobots would arrive at the target in about 0.2 s, which enables nanorobots to detect and follow gradient concentration and thus increases the probability for nanorobots to find the target. In comparison, with random motion, here the nanorobots depict better performance by 23%. For gradient with an “attractant,” the signals allow the nanorobots to find and reach the target in the 3D workspace 46% faster than that with random motion. The improvement in performance is remarkable in terms of response time, hence improving the chances of detecting and eliminating small tumors.
6 Design of nanorobotic systems for cerebral aneurysm 6.1 Nanorobot for intracranial therapy Considering the properties of nanorobots to navigate as blood borne devices, they can aid significant treatment processes of complex diseases in early diagnosis and smart drug delivery (Freitas, 2005; Couvreur et al., 2006). Embedded technology plays an important role in nanorobotic application; through different embedded nanosensors, one can identify medical zones inside the human body. Various computational and numerical simulation techniques are being used that conclude various changes of chemical patterns for brain aneurysm. Various sensing methodologies are offered for nanorobots to identify harmful growth and level of difficulties in medicine, including specialized brain therapies (Leary et al., 2006; Gao et al., 2004). Nowadays, nanorobotic technology is used for treatment of patients from cerebral aneurysm, which solves all the problems.
6.2 Nanorobot hardware architecture Usage of micro devices for medical treatments and instrumentation has investigated various important methods for aneurysm surgery (Ikeda et al., 2005; Roue, 2002). In a similar fashion to how the development of micro technology in the 1980s led to new tools for surgery, emerging nanotechnologies will similarly facilitate further advancements in better diagnosis and new devices for medicine with the help of manufacturing of nanoelectronics (Rosner et al., 2002).
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6.2.1 Manufacturing technology The capacity to assemble nanorobots has resulted from new methodologies used in fabrication and different types of transducers used. Various changes on temperature, chemicals in the bloodstream, and electromagnetic signature effect are some of the key parameters in biomedical need. Nowadays, CMOS technology is used to manufacture components required to enable nanorobots. The combination of nanophotonics and nanotubes is enhancing the levels of resolution (Park et al., 2005a, b) to confirm the designs and to achieve a fruitful implementation; VHDL is being utilized in the integrated circuit manufacturing industry. 6.2.2 Chemical sensor CMOS sensors using nanowires allow new medical applications, which conclude various chemical changes. Sensors with suspended arrays of nanowires assembled into silicon circuits resolve the problem of self-heating and thermal coupling (Fung et al., 2004). In addition, advancements in SOI technology are being used to assemble high-performance logic (Park et al., 2005a, b). Approaches of circuit design to solve bipolar effect and hysteretic variations problems, SOI structures have been confirmed (Bernstein et al., 2003). The best material to design CMOS IC nanosensors is carbon nanotube (Kishimoto et al., 1992). The protein nitric oxide synthase (NOS) offers positive or negative effects upon cells and tissues in cellular living processes. It has also been recognized that the correlations between higher levels of NOS and brain aneurysm have been established (Fukuda et al., 2000). The antibody used for medical nanorobots helps in identifying higher concentrations of proteins that couple NOS forms in the intracellular bloodstream (NOS 2007). Nanobiosensors provide a well-organized technique for nanorobots to identify the exact locations with existence of NOS, which is represented by gradients in the brain enzymes. 6.2.3 Actuator A set of fullerene structures has been presented for nanoactuators (Crowley, 2006). The use of CNTs as conductive structures permits electro-statically driven motions providing forces necessary for nano-manipulation. CNT self-assembly and SOI properties can collectively address CMOS high performance of design and manufacturing nanoelectronics and nanoactuators (Shi et al., 2006). In medical nanorobots, the use of CMOS as an actuator based on biological patterns and CNTs is adopted. In the similar fashion DNA can be used for coupling energy transfer (Schifferli et al., 2002a, b;
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Ding et al., 2006) and proteins may serve as basis for ionic flux with electrical discharge ranges from 50 to 70 mV DC voltage gradients in cell membrane ( Jenkner et al., 2004). An array format based on CNTs and CMOS techniques could be used to achieve nanomanipulators as an embedded system for integrating nanodevices of molecular machines (Zheng et al., 2005). Ion channels can be interfaced with electrochemical signals using sodium for the energy generation necessary for mechanical actuators’ operation ( Jenkner et al., 2004). Actuators are programmed to perform different manipulations, which assists the nanorobot in an active interaction with the bloodstream inside the body. 6.2.4 Power supply In nanorobots, the use CMOS technology for active telemetry and power supply is the best and most secure way to guarantee power supply. The same technique can also be used for bit encoded data transfer from inside the human body (Mohseni et al., 2005). Nanocircuits with tuned electrical properties can work as a chip, providing energy in electromagnetic form to supply at 1.7 mA at 3.3 V. This also permits such tasks with few or no transmission losses (Sauer et al., 2005). RF-based telemetry has shown commendable results in patient monitoring and power transmission with the use of inductive coupling (Eggers et al., 2000). 6.2.5 Data transmission Nanorobot architecture includes a single chip RFID CMOS-based sensor (Ricciardi et al., 2003) Using sensor data transfer as well as read and write data is feasible. Therefore, nanorobot active sonar communication frequencies may reach up to 20 μW@8 Hz at resonance rates with 3 V supply (Horiuchi et al., 2004). For brain aneurysm, chemical nanosensors are embedded in nanorobots to monitor NOS levels. After the last set of events recorded in a pattern array, information can be reflected back by wave resonance. The passive data transfer at 4.5 kHz frequency with approximate 22 μs delays are possible ranges for data communication. In molecular machine architecture, an antenna with 200 nm size for the nanorobot RF communication has been embedded. A small loop planar device is implemented as an electromagnetic pickup, having a good matching on low noise amplifier. The antenna is based on gold nanocrystal with 1.4 nm3, CMOS, and nanoelectronics circuit technologies (Schifferli et al., 2002a, b; Sauer et al., 2005).
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6.3 Implementation and simulation results Nanorobots can be programmed to detect different levels of inducible nitric oxide synthase (iNOS) pattern signals using chemical sensors embedded nanoelectronics. The iNOS proteins serve as medical targets for detecting early stages of aneurysm development. In the NOS subgroups, while eNOS acts as a positive protein, the nNOS is linked to neurodegenerative diseases like Alzheimer’s and Parkinson’s. nNOS plays a distinct role on endothelial cell degenerative changes (Kishimoto et al., 1992). In special cases, nNOS could result in negative effects with nitrosative stress, accelerating intracranial aneurysm rupture. Nanorobots injected in the bloodstream have been used as mobile medical devices. Fig. 1, showing the medical 3D environment, contains clinical data based on key morphological parameters in patients with cerebral aneurysm. Integrated nanosensors, nanobioelectronics, and RF wireless communications (Cavalcanti et al., 2007) are incorporated into the nanorobot model in order to inform changes of gradients for iNOS signals (Fukuda et al., 2000), which assists the medical professional in deciding the treatment plan. The nanorobots are designed at dimensions of 2 μm, which allows them to operate easily inside the body. The nanorobot model comprises of IC nanoelectronics and the platform architecture can instead use cellphones for data transmission and coupling energy. Computations are performed by embedded nanosensors. They are programmed for sensing and detecting NOS concentrations in the bloodstream. Due to background compounds, some detection occurs even without the NOS concentrations specified as the aneurysm target. High precision and a fast response are required for
Fig. 1 Aneurysm morphology—MCA, middle cerebral artery; BT, basilar trunk; BA, basilar artery.
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biosensors. Additionally, false positives of NOS can often occur due to some positive functions of nitric oxide with semicarbazone (pNOS). Chemical detection in a complex and active environment is a vital aspect for nanorobots in the task of interacting within the human body. In the nanorobot architecture, the integrated system contains engines for orientation, drive, and sensing and control mechanisms. Core morphologic features related to brain aneurysm are taken for modeling the study of nanorobots sensing and interaction with blood fluid patterns in the deformed vessel. A critical issue on cerebral aneurysm is to detect and locate the vessel dilation. Nanorobots are required to track the aneurysm growth before a subarachnoid hemorrhage occurs. If an electrochemical sensor detects NOS in low quantities or inside normal gradients, it generates a weak current lower than 50 nA. In such cases, the nanorobot ignores the NOS concentration, assuming it as expected levels of intracranial NOS. However, if the NOS patterns reach concentration higher than 2 μL, it activates the embedded sensor, generating an electric current higher than 90 nA. Every time the activation of nanorobots takes place, an electromagnetic signal is back-propagated in the integrated system platform, which records the nanorobots’ positions at the time of the signal generation. If large numbers of signals are generated, they indicate the early stages of brain aneurysm in the patient. It also informs the doctors about the location of the vessel bulb. The nanorobots provide their respective positions for the moment they detected a high concentration of NOS7. To escape noise distortions and achieve a higher resolution, the system studies a strong evidence of intracranial aneurysm every time it receives back-propagated signals from a total of 100 nanorobots.
7 Medical application of nanorobots Nanorobots are expected to provide novel treatments for patients suffering from various diseases. The advancement will result in an astonishing improvement in the medical arena. Existing advances in bimolecular computing are a promising step towards a future of nanoprocessors of increased intricacy and capabilities. Studies meant at developing biosensors and nanokinetic devices required for medical nanorobotics operation and locomotion is in progress. Application of nanorobots may boost biomedical involvement with slightly invasive surgeries. It will also help patients who
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need continuous monitoring of body functions. Monitoring diabetes and controlling glucose levels for patients will be a possible application of nanorobots. It is also expected to improve the competence of treatments through early diagnosis of probable severe diseases. For instance, nanorobots may be utilized to attach on transmigrating inflammatory cells or white blood cells, thus reaching inflamed tissues faster to help in their healing process. Nanorobots could be used to process specific chemical reactions in the human body as auxiliary devices for wounded organs. Nanorobots will be useful in chemotherapy to fight cancer through specific chemical dosage administration. Similar drug delivery methodology can be adopted to allow nanorobots to deliver anti-HIV or any other drug. Nanorobots could be used to locate and destroy kidney stones. One significant application of medical nanorobots could be the potential to locate atherosclerotic lesions in stenos blood vessels, primarily in coronary circulation, and treat them either mechanically, chemically, or pharmacologically. Organic nanorobots that work on ATP and DNA-based molecular machines are also known as bio-nanorobots. The scheme is to develop ribonucleic acid and adenosine tri-phosphate devices. The usage of tailored microorganisms to achieve a bio-molecular computation, sensing, and actuation for nanorobots is also undergoing experiments. Substitute methods for the development of molecular machines are the inorganic nanorobots. Development of inorganic nanorobots is based on customized nanoelectronics. In comparison to bio-nanorobots, inorganic nanorobots could achieve a much higher intricacy of incorporated nanoscale components. Using new diamondoid rigid materials are a likely advancement that could help in developing new materials for inorganic nanorobots. The nano-build hardware integrated system is discussed here. It includes a combined set of modus operandi and new methodologies from nanotechnology targeted at mechanized manufacturing of nanorobots. It is used in 3D simulation and manufacturing design with integrated nanoelectronics. The challenge of manufacturing nanorobots perhaps will result from new methodologies in fabrication, computation, sensing, and manipulation. Real-time 3D prototyping apparatus are important in nanotechnological developments. This is expected to have direct impact on implementation of new approaches in manufacturing techniques. Simulation can forecast the performance of new nanodevices. Moreover, it will also help nanomechatronics designs and in the test of control and automation approaches. Here in this chapter, the focus is on the applications of nanorobots on cancer treatment and cerebral aneurysms.
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8 Nanorobots in cancer treatment Nanorobots are expected to provide substantial improvements in medicine through the miniaturization from microelectronics to nanoelectronics (Freitas, 2003). Cancer can be treated effectively with current levels of medical technologies and therapy tools. Thus far, a crucial factor in determining the likelihood of a patient with cancer surviving is early diagnosis. The treatment of cancer is reasonably successful when it is detected at least before the metastasis has begun. To achieve successful treatment for patients, professionally targeted drug delivery is also important to decrease the side effects from chemotherapy. Bearing in mind the capability of nanorobots to navigate as blood borne devices, nanorobots can help in targeted drug delivery. Nanorobots with implanted chemical biosensors could be used for detection of tumor cells at an early stage of tumor development in the patient’s body. Nanosensors integrated on the nanorobots can be used to find intensity of E-cadherin signals. Hardware-based architecture for nanobioelectronics is in developmental stage for function of nanorobots in cancer therapy. Analyses and termination for the proposed model have been obtained through real-time 3D simulations.
9 Nanorobots in cerebral aneurysm Endovascular treatment of brain aneurysms, arteriovenous malformations, and arteriovenous fistulas are expected to gain assistance from present research and developments in medical nanorobotics (Drexler, 1986). The first generation of nanotechnological prototypes of molecular machines are being examined and many encouraging device propulsion and sensing methodologies have been recognized (Asimov, 1966; Crichton, 2002). More complex molecular machines like nanorobots, having embedded nanoscopic tools for medical procedures (Sitti et al., 1998), are in the developmental phase. Sensors for biomedical applications are improving through teleoperated surgery and pervasive medicine (Drexler et al., 1991). The same technology provides the basis for manufacturing bimolecular actuators. These tools have pointedly helped the semiconductor industry to achieve faster VLSI developments (Ahuja et al., 2006). It may have a similar impact on the implementation of nanomanufacturing techniques, and on the progress of nanoelectronics. Simulation can foresee performance, help in device modeling, manufacturing analysis,
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nanomechatronics control investigation (Drexler et al., 1991), and hardware designs. For analysis, a real-time simulation based on clinical data is useful, demonstrating sensor and nanorobot behavior capabilities for detection of abnormal vessel dilatation in cases of cerebral aneurysm (Weir et al., 2005).
10 Conclusion This chapter discussed the developments in new manufacturing technologies using nanotechnology because it is an investigative and treatment instrument for patients with cancer and cerebral aneurysm providing tailored treatments with better effectiveness and decreased side effects than those available today. Nano-medicine holds the promise to lead to an earlier diagnosis, better therapy, and improved follow up care, making the healthcare more effective and affordable. This chapter also provided a summary of nanodevices and nanorobotics in medicine. It was a small subset of the massive field of nanotechnology and nanobiotechnology. It is certainly possible that the use of nanorobotic technology will become ubiquitous in medicine within a generation.
11 Forthcoming nanomedicine The arrival of molecular nanotechnology improves the effectiveness, comfort, and speed of forthcoming medical treatments. It will significantly reduce their risk, cost, and invasiveness. Nanotechnology can modify healthcare and human life more intensely than other developments. It is also contributing to shaping the modern industry, broadening the product development in pharma, biotech, diagnostic, and healthcare industries. Prospective healthcare will make use of delicate diagnostics for upgraded health risk assessment. The maximum influence can be anticipated in cardiovascular diseases, cancer, musculoskeletal conditions, neurodegenerative and psychiatric diseases, with the possibility for diabetes and viral infections to be cured with the application of nanotechnology. It will also lead to earlier diagnosis, better therapy, and improved follow-up care, making healthcare more effective and affordable. This technology will also work innovatively in constructing and employing nanorobots effectively for biomedical glitches. Applications of nanorobots in medicine holds a large number of promises from exterminating disease to retreating the ageing process (wrinkles, loss of bone mass, and age-related conditions are all treatable at the cellular level).
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Nanomedicine will permit a more personalized treatment for countless ailments, by taking advantage of the in-depth understanding of diseases on a molecular level. Scientific researchers are on the verge of developing technologies on a scale an order of magnitude smaller than ever before. With the advancement of technology, we will be able to achieve improved control of the world around us and ourselves. Developing the ability to operate the world on a smaller scale has brought revolutionary changes in the scientific discoveries and the world at large. Whether it was the age of microscopes accompanying in the range of bacteriology or commencement of the atomic age with the learning of particle physics, nanotechnology is certain to change many of the patterns with which we think about disease diagnosis, treatment, prevention, and screening related to healthcare. Nanorobotics is evolving extensive possible uses across all fields of medicine and growing the number of therapeutic options available, it is also improving the effectiveness of existing treatments. Nanotechnology will touch our lives in uncountable ways through industries such as telecommunications and agriculture and more.
References Ahuja, S., et al., 2006. A survey on wireless grid computing. J. Supercomput, 3–21. Asimov, I., (1966). Fantastic Voyage. Houghton Mifflin, Boston. Bernstein, K., et al., 2003. Design and CAD challenges in sub-90 nm CMOS technologies. In: ACM Proc. of the Int’l Conf. on Computer Aided Design (ICCAD’03), pp. 129–136. Cavalcanti, A., et al., 2007. Medical nanorobot architecture based on nanobioelectronics. In: Recent Patents on Nanotechnology. Bentham Science, pp. 1–10. Couvreur, P., et al., 2006. Nanotechnology: Intelligent Design to Treat Complex Disease. Pharmaceutical Research Springer, pp. 1417–1450. Crichton, M. (2002). Avon. New York. Crowley, R. (2006). Carbon Nanotube Actuator. 7099071US. Dewdney, A.K., 1988. Nanotechnology—wherein molecular computers control tiny circulatory submarines. Sci. Am., 100–103. Ding, B., et al., 2006. Operation of a DNA robot arm inserted into a 2D DNA crystalline substrate. Science, 1583–1585. Drexler, K.E., 1986. Engines of Creation: The Coming Era of Nanotechnology. Anchor Books, New York. Drexler, K.E., 1992. Nanosystems: Molecular Machinery, Manufacturing, and Computation. John Wiley & Sons (Association of American Publishers "Most Outstanding Computer Science Book"), New York. Drexler, K.E., et al., 1991. Unbounding the Future: The Nanotechnology Revolution. William Morrow, New York. Eggers, T., et al., 2000. Advanced hybrid integrated low-power telemetric pressure monitoring system for biomedical application. In: Proc. of Int’l Conf. on Micro Electro Mechanical Systems, pp. 23–37.
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Freitas, R.A., 1999. Nanomedicine: Basic Capabilities. Landes Bioscience, Georgetown, TX. http://www.nanomedicine.com/NMI.html. Freitas, R.A., 2003. Nanomedicine: Biocompatibility. Landes Bioscience, Georgetown. http://www.nanomedicine.com/NMIIA.htm. Freitas, R.A., 2005. Current status of nanomedicine and medical nanorobotics. J. Comput. Theory Nanosci., 21–25. Fukuda, S., et al., 2000. Prevention of rat cerebral aneurysm formation by inhibition of nitric oxide synthase. Circulation, 101 (21), 2532–2538. Fung, C., et al., 2004. Ultra-low-power polymer thin film encapsulated carbon nanotube thermal sensors. In: IEEE Conf. on Nanotechnology, pp. 158–160. Gao, Q., et al., 2004. Disruption of neural signal transducer and activator of transcription 3 causes obesity, diabetes, infertility, and thermal dysregulation. Proc. Natl. Acad. Sci. USA, 4661–4666. Horiuchi, T., et al., 2004. A time-series novelty detection chip for sonar. Int. J. Robot. Automat. 19 (4), 171–177. Ikeda, S., et al., 2005. In vitro patient-tailored anatomical model of cerebral artery for evaluating medical robots and systems for intravascular neurosurgery. In: IEEE Int’l Conf. on Intelligent Robots and Systems, pp. 1558–1563. Jenkner, M., et al., 2004. Cell-based CMOS sensor and actuator arrays. IEEE J. Solid-State Circ., 2431–2437. Kishimoto, J., et al., 1992. Localization of brain nitric oxide synthase (NOS) to human chromosome 12. Genomics, 802–804. Leary, S., et al., 2006. Toward the emergence of nanoneurosurgery. Part III. Nanomedicine: Targeted nanotherapy, nanosurgery, and progress toward the realization of nanoneurosurgery. Neurosurgery, 1009–1025. Mohseni, P., et al., 2005. Wireless multichannel biopotential recording using and integrated FM telemetry circuit. IEEE Trans. Neural Syst. Rehabil. Eng., 263–271. Park, J. et al. (2005a). Method of Fabricating Nano SOI Wafer and Nano SOI Wafer Fabricated by the Same. 6884694US. Park, J., et al. (2005b). Method of Fabricating Nano SOI Wafer and Nano SOI Wafer Fabricated by the Same. 6884694US. Requicha, A.A.G., et al., 1998. Nanorobotic assembly of two-dimensional structures. In: IEEE International Conference on Robotics and Automation, pp. 3368–3374. Ricciardi, L., et al., 2003. Investigation into the future of RFID in biomedical applications. In: Proc. of SPIE—The Int’l Society for Optical Engineering, pp. 199–209. Rosner, W. et al. (2002). Circuit Configuration Having At Least One Nanoelectronic Component and a Method for Fabricating the Component. 6442042US. Roue, C. (2002). Aneurysm Liner. 6350270US. Sauer, C., et al., 2005. Power harvesting and telemetry in CMOS for implanted devices. IEEE Trans. Circ. Syst., 2605–2613. Schifferli, K., et al., 2002a. Remote electronic control of DNA hybridization through inductive coupling to an attached metal nanocrystal antenna. Nature, 152–156. Schifferli, K., et al., 2002b. Remote electronic control of DNA hybridization through inductive coupling to an attached metal nanocrystal antenna. Nature, 152–156. Shi, J., et al., 2006. Self-assembly of gold nanoparticles onto the surface of multiwall carbon nanotubes functionalized with mercaptobenzene moieties. Springer J. Nanopart. Res., 743–747. Sitti, M., et al., 1998. Tele-nanorobotics using atomic force microscope. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1739–1746. Weir, N.A., et al., 2005. A Review of Research in the Field of Nanorobotics. Sandia National Laboratories.
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Wowk, B., 1988. Cell Repair Technology. Cryonics Magazine, pp. 7–10. Zheng, L., et al., 2005. A large-displacement CMOS micromachined thermal actuator with capacitive position sensing. Asian Solid-State Circ. Conf., 89–92.
Further reading Fukuda, T., et al., 1995. Steering mechanism and swimming experiment of micro mobile robot in water. In: Kawamoto, A., Arai, F., Matsuura, H. (Eds.), IEEE MEMS Micro Electro Mechanical Systems, pp. 300–305.
Architecture and application of nanorobots in medicine Ramna Tripathia, Amit Kumarb and Akhilesh Kumarc a
Department of Physics, THDC-Institute of Hydropower Engineering & Technology, Tehri, India Department of ECE, THDC-Institute of Hydropower Engineering & Technology, Tehri, India Department of Physics, Govt. Girls P. G. College, Lucknow, India
b c
1 Introduction In a prescient talk in 1959, the late Nobel physicist Richard P. Feynman said, “There’s Plenty of Room at the Bottom,” and proposed to make miniature machine apparatuses and use these apparatuses to make still smaller machine apparatuses and so on, all the way down to the atomic level. Feynman was very much clear about the possible medical applications of the new technology. He added: “A friend of mine (Albert R. Hibbs) suggests a very interesting possibility for relatively small machines. He says that, although it is a very wild idea, it would be interesting in surgery if you could swallow the surgeon. You put the mechanical surgeon inside the blood vessel and it goes into the heart and looks around. It finds out which valve is the faulty one and takes a little knife and slices it out. Other small machines might be permanently incorporated in the body to assist some inadequately functioning organ.”
Later, in his subsequent lecture in the same year, Feynman proposed the option of linking with biological cells and said, “We can manufacture an object that maneuvers at that level!” The vision of Feynman come to be a reality after the publishing of a technical paper by Eric Drexler in which he suggested that it might be possible to build nanodevices from biological parts that could examine and repair the cells of a human being. The exploration was followed a decade later by Drexler’s technical book laying the foundations of molecular machines and molecular manufacturing systems (Drexler, 1986, 1992; Drexler et al., 1991) and subsequently supported by Freita’s technical books on medical nanorobotics (Freitas, 1999, 2003, 2005). Control Systems Design of Bio-Robotics and Bio-mechatronics with advanced applications https://doi.org/10.1016/B978-0-12-817463-0.00013-7
© 2020 Elsevier Inc. All rights reserved.
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In the earlier 1990s, very little scientific work was done on nanorobotics, and was mostly based on concept generation, architecture, and modeling. Since then, many research papers have been published on systematic computational and experimental studies on nanorobotics. Nowadays, the field of nanorobotics keeps expanding and many scientists and researchers in their laboratories all over the world are focusing their activities on it. Nanorobotics became known to the public via science fiction movies, television, and books. In 1966, Isaac Asimov published a book entitled Fantastic Voyage, in which he described a minuscule submarine capable of moving through the human bloodstream (Asimov, 1966), while in 2002, in the very popular book, Prey, Michael Crichton introduced a swarm of intelligent nanorobots that threaten humankind (Crichton, 2002). Even though the concept of nanorobotics being described in this book is not at all related with the actual theory of nanorobots, it helped to generate public interest, which is important for the future growth of the field. Nanorobotics is a comparatively new field that grew out of the merging of robotics and nanotechnology during the late 1990s and early 2000s. The term nanorobot was being used by the scientific community in the broadest possible way in the late 1990s, because this term included any type of active structure capable of anyone of the following, or any of them in combination: actuation, sensing, manipulation, propulsion, signaling, information processing, intelligence, and swarm behavior at the nanoscale. The term nanorobot includes large-scale manipulators with nanoscale precision accuracy and manipulation capabilities and micro-scale robotic devices with at least one nanoscale component (Weir et al., 2005). Nanorobots are basically theoretical microscopic devices built on nanometer dimensions (109 m). When nanorobotics has fully realized its potential from the current theoretical stage, nanorobots will work at atomic, molecular, and cellular level to perform tasks in both medical and industrial fields. This came as a natural evolution of the micro-robotics field that grew rapidly in the 1990s and of the nanotechnology field that exploded in the 2000s. Some of the most primitive appearances of the term occur in 1998 in the paper by Requicha et al. that focused on nanorobotic assembly (Requicha et al., 1998); Sitti and Hashimoto’s paper on tele-nanorobotics (Sitti et al., 1998); and in 1999, Freitas’ book on nanomedicine, where one can find a nice historical presentation of the nanorobotic concept for medical applications (Freitas, 1999). Prior to 1998, the term nanorobot had been clearly described by several researchers and was referred to as a “molecular machine,” “nanomachine,” or “cell repair machine” (Wowk, 1988; Dewdney, 1988).
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This chapter emphasizes developments in the evolving domain of nanorobotics in medicine, especially on the design and application of cancer and cerebral aneurysm.
2 Design of nanorobotic systems for cancer therapy Important parameters used for medical nanorobotic architecture and its control activation, along with essential technological background for advance manufacturing hardware for molecular machines are described below.
2.1 Mechanized technology In manufacturing technology, complementary metal oxide semiconductorvery large scale integration (CMOS-VLSI) and verification hardware description language (VHDL) are playing an important role. The CMOS industry is guiding a pathway for assembly processes needed to manufacture components required to enable nanorobots, whereas to confirm the designs and to achieve a fruitful implementation, VHDL is being utilized in the integrated circuit manufacturing industry.
2.2 Chemical sensor In the past decade, production of silicon-based chemical sensor and motion sensor arrays with the use of two-level system architecture hierarchy has been successfully achieved. These sensors are in widespread use from automotive to chemical industries for detection of air, water, element, and pattern recognition through embedded software programming and biomedical uses. Similarly the use of nanotechnology is also groom in this field as nanowires which decreased the estimated cost of energy demanded for data transfer and circuit operation by up to 60%. The CMOS-based biosensors using nanowires as material for circuit assembly can achieve superior efficiency for applications in detecting chemical changes, thus enabling medical treatment with increased precision and effectiveness. CMOS devices of 90 and 45 nm represent breakthrough technology devices that are being applied in manufacturing of nanorobots. Discovery or development of new materials such as strained channel with relaxed SiGe layer can reduce self-heating and improve the performance of nanorobots. In advance manufacturing techniques, silicon on insulator (SOI) technology has also been used to assemble high-performance logic sub 90 nm circuits. Circuit design methods to
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resolve bipolar effects and hysteretic variations based on SOI structures have been verified positively. In addition, chemical nanosensors can be implanted in nanorobots to monitor epithelial cadherin gradients. E-cadherin (or Cadherin-1, or CAM 120/80, or Uvomorulin) is a protein in the human body, encoded by the CDH1 (tumor suppressor) gene, which is designated as cluster of differentiation 324. Evolution of cancer and metastasis is directly proportional of loss of E-cadherin, which means E-cadherin down regulation decreases the strength of cellular adhesion within a tissue, causing an increase in cellular motility, which allows cancer cells to cross the basement membrane and invade surrounding tissues. E-cadherin is also used by pathologists to diagnose different kinds of breast cancer. When compared with invasive ductal carcinoma, E-cadherin expression is markedly reduced or absent in the great majority of invasive lobular carcinomas when studied by immunohistochemistry. Nanorobots programmed for these tasks can perform detailed screening of the whole body of the patient. In this biomedical nanorobotic architecture, cellphones are used to retrieve patient information. A cellular application uses electromagnetic waves to command and detect the current status of nanorobots inside the patient’s body. Contemporary advancement in FinFETs, double-gates, and 3D circuit technologies is capable of accomplishing surprising outcomes, which are expected to develop further.
2.3 Power supply Active telemetry and power supply is the most effective and secure method of sustained energy supply for nanorobots in operation using CMOS. A similar procedure is also suitable for digital bit encoded data transfer from inside the human body. It can be understood that nanocircuits with resonant electric properties can operate as a chip providing electromagnetic energy and supplying 1.7 mA at 3.3 V for power, allowing the operation of many tasks with very few or no power losses during the transmission. By utilizing a techniques that is widely used for commercial applications of radio frequency identification devices (RFID), with the use of inductive coupling, RF-based telemetry procedures have demonstrated encouraging results in patient monitoring and power transmission. In this procedure, the energy savings can be in the ranges of 1 μW when the nanorobot is in inactive modes, and gets activated when signal patterns require it to do so. Some general nanorobotic tasks may require the device only to utilize low amounts of
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power once it has been strategically activated, for example, only 1 mW RF signal required for communication. The easiest way to implement this architecture is by cellphone, which should be uploaded with the control software that includes the communication and energy transfer protocols, gaining both energy and data transfer capabilities.
2.4 Data transmission The implanted devices and integrated sensors inside the human body to transmit health data of patients will provide exceptional advantage in constant medical monitoring. RFID chips have been developed as an integrated circuit device for medicine, and RFID for in vivo data collection and transmission has been successfully tested for electroencephalograms. Many researchers and scientists are working on single chip RFID CMOS-based sensors because CMOS with submicron SoC design may be used for very low power consumption in nanorobotic communication over longer distances through acoustic sensors. Nanorobots’ active sonar communication frequencies may reach up to 20 μW@8 Hz at resonance rates with 3 V supply. In molecular machine architectures, to implant an embedded antenna for nanorobot RF communication with 200 nm size, a small loop planar device is adopted as an electromagnetic pick-up. It also has a good matching on low noise amplifier and is developed on gold nanocrystal with 1.4 nm3 CMOS and nanoelectronics circuit technologies. Frequencies in the range of 1–20 MHz can be fruitfully used in biomedical applications without any damage to the device.
3 System implementation Real-time 3D prototyping and simulation tools have significant benefits in nanotechnological developments because these tools have helped the semiconductor industry to attain faster VLSI developments. Simulation can anticipate the performance and provide support in device design, manufacturing, nanomechatronics control design, and hardware implementation. The simulation includes the nanorobot control design (NCD) software for nanorobot sensing and actuation, whereas nanorobot architectures include integrated nanoelectronics. The nanorobot architecture involves the use of cellphones for the early diagnosis of E-cadherin levels for smart chemotherapy drug delivery and in new tumor detection for cancer treatments. Nanorobots use an RFID CMOS transponder system for in vivo positioning using wellestablished communication protocols that allow tracking information about
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the nanorobot position and this information will help doctors in detecting tiny malignant tissues in the initial stages of development. The exterior of nanorobots is made up of diamondoid material, to which may be attached an artificial glycocalyx surface. The exterior material minimizes fibrinogen (and other blood proteins) adsorption and bioactivity, ensuring sufficient biocompatibility to avoid immune system attack. Various types of molecules have been distinguished by a series of chemotactic biosensors whose binding sites have a different affinity for each kind of molecule. These sensors are also capable of detecting obstacles that might require new trajectory planning for nanorobots. Nanorobots with sensory capabilities are able to detect and identify changes of E-cadherin proteins gradients beyond permissible levels, which guide the nanorobots in detecting tumors even at early stages of cancer. There could be a variety of such sensors, for instance, chemical detection can be very selective for identifying various types of cells by their markers. In acoustic sensing, different frequencies are detected, which have different wavelengths depending on object sizes of attention.
4 Chemical signals inside the body Depending on the requirement of communication in liquid workspaces, acoustic, light, RF and chemical signals are considered as probable alternatives for communication and data transmission. E-cadherin is a chemical signaling, which act as a transmission media between nanorobots. Chemical signals and their interaction with the bloodstream are a very important aspect to manage the application of nanorobots in cancer therapy. The signal sensing of nanorobots for simulated architecture in detecting gradient changes on E-cadherin signals are examined. In order to improve response and bio sensing capabilities, nanorobots maintain positions near the vessel wall instead of floating throughout the vessel in the volume flow. The vein wall is modeled with a grid texture to enable better depth and distance perception in the 3D workspace. Another significant choice in chemical signaling is the measurement of time and detection of threshold at which the signal is considered to be received. Because of background concentration, some detection occurs even in the absence of the target signal. With threshold, diffusive capture rate (α) is used, for a sphere of radius (R) in a region with concentration as (the concentration for other shapes such as cylinders is about the same): α ¼ 4πDRC
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With autonomous random motions for the molecules, detection over a time interval (Δt) is a Poisson process with mean value αΔt. Table 1 shows the different parameters with chemical signals that one can use to find out the variables related with this concept. Scientists have discovered that, with the plaque on the vessel wall, fluid velocity near the target is lower than the average velocity. When the nanorobot first detects a tumor for medical treatment, the nanorobot is programmed to attach on the tumor cell. The nanorobotic architecture is designed to send wireless communication about the accurate position of the tumor to the doctors. Then a predefined number of other nanorobots to support in perceptive chemotherapeutic action with precise drug delivery above the tumor are called for by sending signals. In a similar manner to quorum sensing in bacteria, it starts from monitoring the concentration of signals, chemical substances for near communication will attract or repeal nanorobots, and also estimates the number of nanorobots at the target. Due to this, nanorobots stop attracting other nanorobots when a sufficient number of nanorobots have responded to the initial signal. The amount of nanorobots can be changed depending on the stage of cancer and the tumor size, and may be defined by the oncologist based on the information received from the nanorobots through RF electromagnetic waves. The nanorobots at the plaque emit a different signal than others not already at the target, which is interpreted as an indication that others no longer need to respond. This mechanism allows them to be free to further search for other malignant tissues inside the body. Nanorobots will empower drug delivery and are also loaded with therapeutic
Table 1 Chemical signal and parameters. Chemical signals
Production rate (Q) Diffusion coefficient (D) Background concentration (C)
104 molecules/s 100 μm2/s 6 103 molecules/(μm)3
Parameters
Values
Average fluid velocity (v) Vessel diameter (d) Workspace length (L) Density of cells Nanorobot
1000 μm/s 20 μm 50 μm 2.5 103 cell/(μm)3 2 μm3
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chemicals, preventing the cancer from spreading further. The following control mechanisms are being considered: • Random: Nanorobots moving inactively with the fluid reaching the target only if they bump into it due to Brownian motion. • Follow gradient: Nanorobots monitor concentration intensity of E-cadherin signals when detected; they measure and follow the gradient until they reach the target. If the gradient estimate finds no additional signal in 50 ms, the nanorobot considers the signal to be a false positive signal and continues flowing with the fluid. • Follow gradient with attractant: In addition to the previous mechanism, nanorobots arriving at the target release a different chemical signal, which is used by others to improve their ability to find the target. This mechanism involving peer-to-peer communication amongst the nanorobots is highly pertinent for improving nanorobotic performance.
5 Simulator results Consider a fluid moving with uniform velocity (v) in the positive x axis direction. It contains a point source of chemical production rate (Q) in molecules per second. The diffusion coefficient is represented by D, and the diffusion equation is: Dr2 C ¼ v∂C=∂x With the boundary conditions of a steady point source at the origin and distance to the chemical signal source (r ¼ √ x2 + y2 + z2) and no net flux across the boundary plane (y ¼ 0), determines the steady-state concentration (C), i.e., time during which concentration (molecules/μm3) remains stable or consistent, at point (x, y, z) is: C ðx, y, zÞ ¼ ðQ=2πDr ÞevðrxÞ=2D In nanorobotic behavior the fluid flow pushes the concentration of diffusing signal downstream. Subsequently, a nanorobot at more than a few microns away from the source won’t detect the signal while it is still relatively near the source. By taking the parameters from Table 1, one can detect an average higher signal concentration within about 10 ms when nanorobots are close enough. Thus, keeping their motion near the vessel wall, the signal detection happens after nanorobots have moved around 10 μm past the source. Thus, nearly
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five nanorobots per second arrive at the tumor cell in the small venule, which is one among many types of vessels present in the human body. A design trade-off for chemical signals the nanorobots could release is designed by the equation C(x, y, z) ¼ (Q/2πDr)e v(r x)/2D. Additional signals will use other molecules, which could, by design, have a different diffusion coefficient to use instead of the diffusion coefficient associated with the chemical from the target. From this equation, the effect of the fluid motion becomes significant at distances; this means that faster diffusion results in lower concentrations, demanding more time for other nanorobots to determine gradients. In future, if the signals are increasing in a steady, constant, and progressive manner, then chemical diffusion could be more efficient for nanorobotic communication. The nanorobots strike the target, if passing inside the human body, with a speed of nearly 0.1 μm. The nanorobots crossing within a few microns often detect the signal, which spreads a bit further upstream and away from the single tumor due to the slow fluid motion near the venule’s wall and the cell’s motion. Nanorobots flowing closer to the wall also benefit from slower fluid motion near the walls by having more time to detect signals. An “attractant” signal with the same value of D as the original signal has been used. Each nanorobot can release at one-tenth the rate of the target over the time. Individual performance has been observed throughout a set of analyses obtained from the NCD software, in which nanorobots use chemical sensors as the communication technique to interact dynamically in a 3D environment and to achieve a positive collective coordination. The virtual environment comprised of a small venule vessel that contains nanorobots, red blood cells (RBCs), and a single tumor cell, which is the target area on the vessel wall. Here, the target area is overlapped by the RBCs. Table 2 provides a summary and comparison of the control techniques evaluated using the NCD simulator with the time required for 10 nanorobots and 20 nanorobots to identify and reach the target. Each value is the mean of 30 repetitions in simulation, with standard deviation in parentheses. The error estimate for these mean values is Table 2 Nanorobots: times in seconds to reach the target.
Control method Random motion Follow gradient Gradient with “attractant”
Nanorobots (10) 0.73 (0.18) 0.54 (0.17) 0.46 (0.13)
Nanorobots (20) 1.47 (0.28) 1.14 (0.24) 0.79 (0.14)
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√ 30 times smaller than the standard deviations listed here. For comparison, if every nanorobot passing through the vessel found the target, 20 nanorobots would arrive at the target in about 0.2 s, which enables nanorobots to detect and follow gradient concentration and thus increases the probability for nanorobots to find the target. In comparison, with random motion, here the nanorobots depict better performance by 23%. For gradient with an “attractant,” the signals allow the nanorobots to find and reach the target in the 3D workspace 46% faster than that with random motion. The improvement in performance is remarkable in terms of response time, hence improving the chances of detecting and eliminating small tumors.
6 Design of nanorobotic systems for cerebral aneurysm 6.1 Nanorobot for intracranial therapy Considering the properties of nanorobots to navigate as blood borne devices, they can aid significant treatment processes of complex diseases in early diagnosis and smart drug delivery (Freitas, 2005; Couvreur et al., 2006). Embedded technology plays an important role in nanorobotic application; through different embedded nanosensors, one can identify medical zones inside the human body. Various computational and numerical simulation techniques are being used that conclude various changes of chemical patterns for brain aneurysm. Various sensing methodologies are offered for nanorobots to identify harmful growth and level of difficulties in medicine, including specialized brain therapies (Leary et al., 2006; Gao et al., 2004). Nowadays, nanorobotic technology is used for treatment of patients from cerebral aneurysm, which solves all the problems.
6.2 Nanorobot hardware architecture Usage of micro devices for medical treatments and instrumentation has investigated various important methods for aneurysm surgery (Ikeda et al., 2005; Roue, 2002). In a similar fashion to how the development of micro technology in the 1980s led to new tools for surgery, emerging nanotechnologies will similarly facilitate further advancements in better diagnosis and new devices for medicine with the help of manufacturing of nanoelectronics (Rosner et al., 2002).
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6.2.1 Manufacturing technology The capacity to assemble nanorobots has resulted from new methodologies used in fabrication and different types of transducers used. Various changes on temperature, chemicals in the bloodstream, and electromagnetic signature effect are some of the key parameters in biomedical need. Nowadays, CMOS technology is used to manufacture components required to enable nanorobots. The combination of nanophotonics and nanotubes is enhancing the levels of resolution (Park et al., 2005a, b) to confirm the designs and to achieve a fruitful implementation; VHDL is being utilized in the integrated circuit manufacturing industry. 6.2.2 Chemical sensor CMOS sensors using nanowires allow new medical applications, which conclude various chemical changes. Sensors with suspended arrays of nanowires assembled into silicon circuits resolve the problem of self-heating and thermal coupling (Fung et al., 2004). In addition, advancements in SOI technology are being used to assemble high-performance logic (Park et al., 2005a, b). Approaches of circuit design to solve bipolar effect and hysteretic variations problems, SOI structures have been confirmed (Bernstein et al., 2003). The best material to design CMOS IC nanosensors is carbon nanotube (Kishimoto et al., 1992). The protein nitric oxide synthase (NOS) offers positive or negative effects upon cells and tissues in cellular living processes. It has also been recognized that the correlations between higher levels of NOS and brain aneurysm have been established (Fukuda et al., 2000). The antibody used for medical nanorobots helps in identifying higher concentrations of proteins that couple NOS forms in the intracellular bloodstream (NOS 2007). Nanobiosensors provide a well-organized technique for nanorobots to identify the exact locations with existence of NOS, which is represented by gradients in the brain enzymes. 6.2.3 Actuator A set of fullerene structures has been presented for nanoactuators (Crowley, 2006). The use of CNTs as conductive structures permits electro-statically driven motions providing forces necessary for nano-manipulation. CNT self-assembly and SOI properties can collectively address CMOS high performance of design and manufacturing nanoelectronics and nanoactuators (Shi et al., 2006). In medical nanorobots, the use of CMOS as an actuator based on biological patterns and CNTs is adopted. In the similar fashion DNA can be used for coupling energy transfer (Schifferli et al., 2002a, b;
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Ding et al., 2006) and proteins may serve as basis for ionic flux with electrical discharge ranges from 50 to 70 mV DC voltage gradients in cell membrane ( Jenkner et al., 2004). An array format based on CNTs and CMOS techniques could be used to achieve nanomanipulators as an embedded system for integrating nanodevices of molecular machines (Zheng et al., 2005). Ion channels can be interfaced with electrochemical signals using sodium for the energy generation necessary for mechanical actuators’ operation ( Jenkner et al., 2004). Actuators are programmed to perform different manipulations, which assists the nanorobot in an active interaction with the bloodstream inside the body. 6.2.4 Power supply In nanorobots, the use CMOS technology for active telemetry and power supply is the best and most secure way to guarantee power supply. The same technique can also be used for bit encoded data transfer from inside the human body (Mohseni et al., 2005). Nanocircuits with tuned electrical properties can work as a chip, providing energy in electromagnetic form to supply at 1.7 mA at 3.3 V. This also permits such tasks with few or no transmission losses (Sauer et al., 2005). RF-based telemetry has shown commendable results in patient monitoring and power transmission with the use of inductive coupling (Eggers et al., 2000). 6.2.5 Data transmission Nanorobot architecture includes a single chip RFID CMOS-based sensor (Ricciardi et al., 2003) Using sensor data transfer as well as read and write data is feasible. Therefore, nanorobot active sonar communication frequencies may reach up to 20 μW@8 Hz at resonance rates with 3 V supply (Horiuchi et al., 2004). For brain aneurysm, chemical nanosensors are embedded in nanorobots to monitor NOS levels. After the last set of events recorded in a pattern array, information can be reflected back by wave resonance. The passive data transfer at 4.5 kHz frequency with approximate 22 μs delays are possible ranges for data communication. In molecular machine architecture, an antenna with 200 nm size for the nanorobot RF communication has been embedded. A small loop planar device is implemented as an electromagnetic pickup, having a good matching on low noise amplifier. The antenna is based on gold nanocrystal with 1.4 nm3, CMOS, and nanoelectronics circuit technologies (Schifferli et al., 2002a, b; Sauer et al., 2005).
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6.3 Implementation and simulation results Nanorobots can be programmed to detect different levels of inducible nitric oxide synthase (iNOS) pattern signals using chemical sensors embedded nanoelectronics. The iNOS proteins serve as medical targets for detecting early stages of aneurysm development. In the NOS subgroups, while eNOS acts as a positive protein, the nNOS is linked to neurodegenerative diseases like Alzheimer’s and Parkinson’s. nNOS plays a distinct role on endothelial cell degenerative changes (Kishimoto et al., 1992). In special cases, nNOS could result in negative effects with nitrosative stress, accelerating intracranial aneurysm rupture. Nanorobots injected in the bloodstream have been used as mobile medical devices. Fig. 1, showing the medical 3D environment, contains clinical data based on key morphological parameters in patients with cerebral aneurysm. Integrated nanosensors, nanobioelectronics, and RF wireless communications (Cavalcanti et al., 2007) are incorporated into the nanorobot model in order to inform changes of gradients for iNOS signals (Fukuda et al., 2000), which assists the medical professional in deciding the treatment plan. The nanorobots are designed at dimensions of 2 μm, which allows them to operate easily inside the body. The nanorobot model comprises of IC nanoelectronics and the platform architecture can instead use cellphones for data transmission and coupling energy. Computations are performed by embedded nanosensors. They are programmed for sensing and detecting NOS concentrations in the bloodstream. Due to background compounds, some detection occurs even without the NOS concentrations specified as the aneurysm target. High precision and a fast response are required for
Fig. 1 Aneurysm morphology—MCA, middle cerebral artery; BT, basilar trunk; BA, basilar artery.
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biosensors. Additionally, false positives of NOS can often occur due to some positive functions of nitric oxide with semicarbazone (pNOS). Chemical detection in a complex and active environment is a vital aspect for nanorobots in the task of interacting within the human body. In the nanorobot architecture, the integrated system contains engines for orientation, drive, and sensing and control mechanisms. Core morphologic features related to brain aneurysm are taken for modeling the study of nanorobots sensing and interaction with blood fluid patterns in the deformed vessel. A critical issue on cerebral aneurysm is to detect and locate the vessel dilation. Nanorobots are required to track the aneurysm growth before a subarachnoid hemorrhage occurs. If an electrochemical sensor detects NOS in low quantities or inside normal gradients, it generates a weak current lower than 50 nA. In such cases, the nanorobot ignores the NOS concentration, assuming it as expected levels of intracranial NOS. However, if the NOS patterns reach concentration higher than 2 μL, it activates the embedded sensor, generating an electric current higher than 90 nA. Every time the activation of nanorobots takes place, an electromagnetic signal is back-propagated in the integrated system platform, which records the nanorobots’ positions at the time of the signal generation. If large numbers of signals are generated, they indicate the early stages of brain aneurysm in the patient. It also informs the doctors about the location of the vessel bulb. The nanorobots provide their respective positions for the moment they detected a high concentration of NOS7. To escape noise distortions and achieve a higher resolution, the system studies a strong evidence of intracranial aneurysm every time it receives back-propagated signals from a total of 100 nanorobots.
7 Medical application of nanorobots Nanorobots are expected to provide novel treatments for patients suffering from various diseases. The advancement will result in an astonishing improvement in the medical arena. Existing advances in bimolecular computing are a promising step towards a future of nanoprocessors of increased intricacy and capabilities. Studies meant at developing biosensors and nanokinetic devices required for medical nanorobotics operation and locomotion is in progress. Application of nanorobots may boost biomedical involvement with slightly invasive surgeries. It will also help patients who
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need continuous monitoring of body functions. Monitoring diabetes and controlling glucose levels for patients will be a possible application of nanorobots. It is also expected to improve the competence of treatments through early diagnosis of probable severe diseases. For instance, nanorobots may be utilized to attach on transmigrating inflammatory cells or white blood cells, thus reaching inflamed tissues faster to help in their healing process. Nanorobots could be used to process specific chemical reactions in the human body as auxiliary devices for wounded organs. Nanorobots will be useful in chemotherapy to fight cancer through specific chemical dosage administration. Similar drug delivery methodology can be adopted to allow nanorobots to deliver anti-HIV or any other drug. Nanorobots could be used to locate and destroy kidney stones. One significant application of medical nanorobots could be the potential to locate atherosclerotic lesions in stenos blood vessels, primarily in coronary circulation, and treat them either mechanically, chemically, or pharmacologically. Organic nanorobots that work on ATP and DNA-based molecular machines are also known as bio-nanorobots. The scheme is to develop ribonucleic acid and adenosine tri-phosphate devices. The usage of tailored microorganisms to achieve a bio-molecular computation, sensing, and actuation for nanorobots is also undergoing experiments. Substitute methods for the development of molecular machines are the inorganic nanorobots. Development of inorganic nanorobots is based on customized nanoelectronics. In comparison to bio-nanorobots, inorganic nanorobots could achieve a much higher intricacy of incorporated nanoscale components. Using new diamondoid rigid materials are a likely advancement that could help in developing new materials for inorganic nanorobots. The nano-build hardware integrated system is discussed here. It includes a combined set of modus operandi and new methodologies from nanotechnology targeted at mechanized manufacturing of nanorobots. It is used in 3D simulation and manufacturing design with integrated nanoelectronics. The challenge of manufacturing nanorobots perhaps will result from new methodologies in fabrication, computation, sensing, and manipulation. Real-time 3D prototyping apparatus are important in nanotechnological developments. This is expected to have direct impact on implementation of new approaches in manufacturing techniques. Simulation can forecast the performance of new nanodevices. Moreover, it will also help nanomechatronics designs and in the test of control and automation approaches. Here in this chapter, the focus is on the applications of nanorobots on cancer treatment and cerebral aneurysms.
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8 Nanorobots in cancer treatment Nanorobots are expected to provide substantial improvements in medicine through the miniaturization from microelectronics to nanoelectronics (Freitas, 2003). Cancer can be treated effectively with current levels of medical technologies and therapy tools. Thus far, a crucial factor in determining the likelihood of a patient with cancer surviving is early diagnosis. The treatment of cancer is reasonably successful when it is detected at least before the metastasis has begun. To achieve successful treatment for patients, professionally targeted drug delivery is also important to decrease the side effects from chemotherapy. Bearing in mind the capability of nanorobots to navigate as blood borne devices, nanorobots can help in targeted drug delivery. Nanorobots with implanted chemical biosensors could be used for detection of tumor cells at an early stage of tumor development in the patient’s body. Nanosensors integrated on the nanorobots can be used to find intensity of E-cadherin signals. Hardware-based architecture for nanobioelectronics is in developmental stage for function of nanorobots in cancer therapy. Analyses and termination for the proposed model have been obtained through real-time 3D simulations.
9 Nanorobots in cerebral aneurysm Endovascular treatment of brain aneurysms, arteriovenous malformations, and arteriovenous fistulas are expected to gain assistance from present research and developments in medical nanorobotics (Drexler, 1986). The first generation of nanotechnological prototypes of molecular machines are being examined and many encouraging device propulsion and sensing methodologies have been recognized (Asimov, 1966; Crichton, 2002). More complex molecular machines like nanorobots, having embedded nanoscopic tools for medical procedures (Sitti et al., 1998), are in the developmental phase. Sensors for biomedical applications are improving through teleoperated surgery and pervasive medicine (Drexler et al., 1991). The same technology provides the basis for manufacturing bimolecular actuators. These tools have pointedly helped the semiconductor industry to achieve faster VLSI developments (Ahuja et al., 2006). It may have a similar impact on the implementation of nanomanufacturing techniques, and on the progress of nanoelectronics. Simulation can foresee performance, help in device modeling, manufacturing analysis,
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nanomechatronics control investigation (Drexler et al., 1991), and hardware designs. For analysis, a real-time simulation based on clinical data is useful, demonstrating sensor and nanorobot behavior capabilities for detection of abnormal vessel dilatation in cases of cerebral aneurysm (Weir et al., 2005).
10 Conclusion This chapter discussed the developments in new manufacturing technologies using nanotechnology because it is an investigative and treatment instrument for patients with cancer and cerebral aneurysm providing tailored treatments with better effectiveness and decreased side effects than those available today. Nano-medicine holds the promise to lead to an earlier diagnosis, better therapy, and improved follow up care, making the healthcare more effective and affordable. This chapter also provided a summary of nanodevices and nanorobotics in medicine. It was a small subset of the massive field of nanotechnology and nanobiotechnology. It is certainly possible that the use of nanorobotic technology will become ubiquitous in medicine within a generation.
11 Forthcoming nanomedicine The arrival of molecular nanotechnology improves the effectiveness, comfort, and speed of forthcoming medical treatments. It will significantly reduce their risk, cost, and invasiveness. Nanotechnology can modify healthcare and human life more intensely than other developments. It is also contributing to shaping the modern industry, broadening the product development in pharma, biotech, diagnostic, and healthcare industries. Prospective healthcare will make use of delicate diagnostics for upgraded health risk assessment. The maximum influence can be anticipated in cardiovascular diseases, cancer, musculoskeletal conditions, neurodegenerative and psychiatric diseases, with the possibility for diabetes and viral infections to be cured with the application of nanotechnology. It will also lead to earlier diagnosis, better therapy, and improved follow-up care, making healthcare more effective and affordable. This technology will also work innovatively in constructing and employing nanorobots effectively for biomedical glitches. Applications of nanorobots in medicine holds a large number of promises from exterminating disease to retreating the ageing process (wrinkles, loss of bone mass, and age-related conditions are all treatable at the cellular level).
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Nanomedicine will permit a more personalized treatment for countless ailments, by taking advantage of the in-depth understanding of diseases on a molecular level. Scientific researchers are on the verge of developing technologies on a scale an order of magnitude smaller than ever before. With the advancement of technology, we will be able to achieve improved control of the world around us and ourselves. Developing the ability to operate the world on a smaller scale has brought revolutionary changes in the scientific discoveries and the world at large. Whether it was the age of microscopes accompanying in the range of bacteriology or commencement of the atomic age with the learning of particle physics, nanotechnology is certain to change many of the patterns with which we think about disease diagnosis, treatment, prevention, and screening related to healthcare. Nanorobotics is evolving extensive possible uses across all fields of medicine and growing the number of therapeutic options available, it is also improving the effectiveness of existing treatments. Nanotechnology will touch our lives in uncountable ways through industries such as telecommunications and agriculture and more.
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Further reading Fukuda, T., et al., 1995. Steering mechanism and swimming experiment of micro mobile robot in water. In: Kawamoto, A., Arai, F., Matsuura, H. (Eds.), IEEE MEMS Micro Electro Mechanical Systems, pp. 300–305.